Towards Discrete Exterior Calculus and Discrete Mechanics for Numerical Relativity
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1 Towards Discrete Exterior Calculus and Discrete Mechanics for Numerical Relativity Melvin Leok Mathematics, University of Michigan, Ann Arbor. Joint work with Mathieu Desbrun, Anil Hirani, and Jerrold Marsden. IPAM Workshop on Relativistic Astrophysics, May mleok/ Mathematics, University of Michigan, Ann Arbor
2 Geometry and Numerical Methods Dynamical equations preserve structure Many continuous systems of interest have properties that are conserved by the flow: Energy Symmetries, Reversibility, Monotonicity Momentum - Angular, Linear, Kelvin Circulation Theorem, Constraint Equations in Relativity Symplectic Form At other times, the equations themselves are defined on a manifold, such as a Lie group, or more general configuration manifold of a mechanical system, and the discrete trajectory we compute should remain on this manifold, since the equations may not be well-defined off the surface. 2
3 3 Motivation: Geometric Integration Main Goal of Geometric Integration: Structure preservation in order to reproduce long time behavior. Role of Discrete Structure-Preservation: Discrete conservation laws impart long time numerical stability to computations, since the structure-preserving algorithm exactly conserves a discrete quantity that is always close to the continuous quantity we are interested in.
4 4 Geometric Integration: Energy Stability Energy stability for symplectic integrators Control on global error Continuous energy Isosurface Discrete energy Isosurface
5 5 Discrete Mechanics Discrete Variational Principle q( t) varied curve qi varied point Q Q q( b) qn q( a) q( t) q0 qi Discrete Lagrangian L d h 0 L (q(t), q(t)) dt Discrete Euler-Lagrange equation D 2 L d (q 0, q 1 ) + D 1 L d (q 1, q 2 ) = 0 The discrete flows are symplectic and momentum preserving.
6 Geometric Integration: Energy Stability Energy behavior for conservative and dissipative systems Midpoint Newmark Energy Benchmark Variational Explicit Newmark non-variational Runge-Kutta Energy Variational Runge-Kutta Benchmark Time (a) Conservative mechanics Time (b) Dissipative mechanics
7 7 Motivation Discrete Geometry and Computer Graphics Desire robust computation on discrete meshes. Many applications require differential geometric concepts: PDE based Image Processing on Curved Surfaces. Smoothing, simplification, and remeshing of triangulated surfaces. Little consensus on how to compute basic surface properties like normals and curvature.
8 8 Discrete Geometry and Computer Graphics Mean, Gaussian, and Principal Curvatures
9 Discrete Geometry and Accurate Simulation Exact Sequences and Spectral Properties Compatible discretizations of differential operators preserve the exact sequence properties of the corresponding continuous operators. 9 R H 1 (Ω) grad H 1 (curl, Ω) curl H 1 (div, Ω) div L 2 (Ω, R) 0 These exactness properties turn out to be important in ensuring that the corresponding numerical schemes are stable. In computing the modes of an electromagnetic cavity, compatible discretizations yield more accurate eigenvalues.
10 Discrete Geometry and Accurate Simulation Exact Sequences and Spectral Properties Compatible discretization may be important for accurate prediction of gravitational wave modes. 10 Computed using edge elements (compatible discretization) Computed using linear finite elements
11 11 Discrete Exterior Calculus Motivating Application Laplace-Beltrami Operator Relevant Formalism Primal and Dual Complexes Differential Forms and Exterior Derivative Hodge Star and Codifferential
12 Why bother? Primal and Dual Complexes Essential for capturing the inherent geometry of the problem. In geometric mechanics, we have to conscious of whether an object is in the tangent bundle or the cotangent bundle. While we can identify these spaces through the metric, we do this naïvely at our own peril. This results in a corresponding distinction at the level of discrete mechanics, where objects may be naturally primal or dual. A new idea? Arises implicitly or explicitly in various schemes, including finite volume, finite element and finite difference methods. 12
13 13 Primal and Dual Meshes in FV, FE, FD Methods Finite Volume Method Explicit use of two staggered discretization grids. Voronoi dual mesh obtained by associating to each point the volume that is closer to that point than any other point.
14 14 Primal and Dual Meshes in FV, FE, FD Methods Finite Element Method Can arise implicitly by choice of shape functions Application to computational electromagnetism hints at underlying geometry, since the choice of shape functions for field quantities depend on duality relations between the various field variables.
15 Primal and Dual Meshes in FV, FE, FD Methods Computational Electromagnetism using Finite Elements Field Variable component x y t φ A x A y E x E y B z The choice of tensor product shape functions in two dimensional Cartesian traverse magnetic (TM) model. 15
16 Primal and Dual Meshes in FV, FE, FD Methods Finite Difference Method Primal and dual meshes arise in integration schemes such as the Verlet leapfrog method. v n+ 1 2 = v n f n m t q n+1 = q n + v n+ 1 2 t 16 q n 1 v n 1 2 q n v n+ 1 2 q n+1 v n+ 3 2
17 Primal and Dual Meshes in FV, FE, FD Methods Finite Difference Method Staggered Meshes in Space-time used in the Constrained Transport (CT) Method for Magnetohydrodynamics, implemented in ZEUS- 2D. B z Bx A z By A y A x Ḃz Ḃ x E Ḃ z y E y E x t 0 t 1/2 t 1 B z Bx A z By A y A x 17
18 Simplices Primal Simplicial Complex A k-simplex is the convex span of k + 1 linearly independent vectors. A k-chain is a formal sum of k-simplices. The group of k-chains is denoted C k (K). Example of chains, 18
19 19 Dual Cell Complex Constructing the Dual Complex The circumcentric duality operator is given by (σ p [ ] ) = c(σ p ), c(σ p+1 ),..., c(σ n ) σ p σ p+1... σ n ɛ σ p,...,σ n Associates a k-simplex to a (n k)-cell. Satisfies the property, (σ k ) = ( 1) k(n k) σ k. Will be used in constructing the Hodge Star for discrete differential forms.
20 20 Examples of Primal Simplices and Dual Cells Primal Simplex Dual Cell σ 0, 0-simplex σ 0, 3-cell σ 1, 1-simplex σ 1, 2-cell
21 21 Examples of Primal Simplices and Dual Cells Primal Simplex Dual Cell σ 2, 2-simplex σ 2, 1-cell σ 3, 3-simplex σ 3, 0-cell
22 Differential Forms and Exterior Derivative Cochains and Differential Forms A Discrete Differential Form is a cochain on the simplicial complex. That is, Ω k d (K) = Ck (K; R) = Hom(C k (K), R). It is a linear functional on simplices, and it defined by assigning a number to each simplex. To discretize a continuous differential form into a discrete differential form, we assign a number to each simplex by integration, αd k, σk = σ k αk. After the discretization step, we can discard the continuous differential form. 22
23 Differential Forms and Exterior Derivative Exterior Derivative The Exterior Derivative is defined by using the Generalized Stokes Theorem, dα k, σ k+1 = α k, σ k+1. where the boundary operator k : C k (K) C k 1 (K) is given by, k k σ k = ([v 0, v 1,..., v k ]) = ( 1) i [v 0,..., ˆv i,..., v p ] As an example, ( ) i=0 =, where clearly, orientation must be carefully taken into account. 23
24 Hodge Star Hodge Star and Codifferential The discrete Hodge Star is a map : Ω k d (K) Ωn k d ( K). For a k-simplex σ k and a discrete k-form α k, Codifferential 1 σ k αk, σ k = 1 σ k αk, σ k. The discrete codifferential operator δ : Ω k+1 d (K) Ω k d (K) is defined by δ(ω 0 d (K)) = 0 and on (k + 1)-discrete forms to be, δβ = ( 1) nk+1 d β. 24
25 Laplace-Beltrami Application The Laplace-Beltrami operator is a special case of the more general Laplace-deRham operator = dδ + δd. 1 σ 0 f, σ0 = δdf, σ 0 = d df, σ 0 = 1 σ 0 d df, σ0 = 1 σ 0 df, ( σ0 ) = 1 σ 0 df, σ 1 σ 1 σ 0 V 25
26 Application Laplace-Beltrami = 1 σ 0 df, σ 1 σ 1 σ 0 = 1 σ 1 σ 0 σ 1 df, σ1 = 1 σ 0 σ 1 σ 0 σ 1 σ 0 σ 1 σ 1 (f(v) f(σ0 )) This recovers a formula involving cotangents found by Meyer et al.using a variational approach. V 26
27 Variational Formulation of Harmonic Functions Inner Product for Differential Forms Need an inner product for forms, α, β = M α β. At a discrete level, this involves a primal-dual wedge product, which we only have for the case of primal k forms and dual (n k)-forms, α k β k, V σ k = V σ k σ k σ k αk, σ k β k, σ k = 1 n σ k σ k αk, σ k β k, σ k. 27
28 Variational Formulation of Harmonic Functions Discrete Variational Principle A discrete Harmonic function is a stationary point of the following discrete Lagrangian, L = df df, V σ 1. σ 1 K The corresponding Euler-Lagrange equation is, 2 σ 1 n σ 1 df, σ1 = 0. σ 1 =[v 1,v 0 ] v 0 This means that the variational formulation of discrete Harmonic functions is equivalent to the formulation in terms of the Laplace- Beltrami operator. 28
29 Discrete Formulation Discrete Electromagnetism Covariant formulation using the 4-vector potential as the fundamental variable. 3+1 tensor product discretization, K N. Lorentzian metric structure causes the Laplace- Beltrami operator to be a hyperbolic operator as opposed to an elliptic operator. Equivalent expressions when applying discretization at the level of the variational principle, and Space at the level of the equations. Discretizing either the Euler-Lagrange equations or the Lagrangian using DEC yields the same Discrete Euler-Lagrange equations. Time 29
30 Discrete Electromagnetism The effect of the Lorentzian metric on the Hodge Star The discrete Hodge star for prismal complexes in Lorentzian space is given by, 1 σ k αk, σ k = κ(σ k ) 1 σ k αk, σ k, where the causality sign κ(σ k ) is defined to be +1 if all the edges of σ k are spacelike, and 1 otherwise. 30 σ 2 κ(σ 2 )
31 31 Multisymplectic Geometry Geometry and Variational Mechanics Base space X. The independent variables, typically (n+1)-spacetime, denoted by (x 0,..., x n ). Configuration bundle. π : Y X. Configuration q : X Y. Gives the field variables over each spacetime point. First jet extension J 1 Y. Consists of the first partials of the field variables with respect to the independent variables. Lagrangian density L : J 1 Y Ω n+1 (X ). Action integral S(q) = X L(j1 q). Hamilton s principle δs = 0.
32 Towards Numerical Relativity Lagrangian Formulation of Relativity Introduce a Lagrangian density that is a 4-form on space-time, as suggested by Frank Estabrook. Discretize the action using Discrete Exterior Calculus. Gauge Invariance and Constraints The invariance of the discrete Lagrangian under gauge transformations yields a discrete Noether s theorem. Discrete analogues of the constraint equations are automatically satisfied, thereby giving long time numerical stability. 32
33 Summary Conclusion Incorporates discrete forms, vector fields, and related operators Construction of canonical discrete differential operators Applications to Laplace-Beltrami operator, Harmonic maps, and Electromagnetism Constraint equations are Noether quantities that arise from the gauge invariance of the Lagangian formulation of relativity. 33
34 Mathematics, University of Michigan, Ann Arbor Slides available at, mleok/ipam dec.pdf
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